We're open-sourcing the first publicly available blood detection model: dataset, weights, and CLI [P] [R]

**BloodshotNet** is an open-source blood detection model releasing dataset, weights (YOLO26 small and nano variants, AGPL-3.0), and a CLI tool, trained on 23k+ annotated images spanning forensic, combat sports, horror, and surgical content with a hard-negative slice to suppress false positives. The small model achieves ~0.8 precision and ~0.6 recall at 40+ FPS on CPU, making it viable for real-time content moderation pipelines without GPU infrastructure. The recall figure (0.6) indicates meaningful miss rate that practitioners should account for when positioning this as a first-pass filter rather than a sole enforcement layer in Trust & Safety workflows.